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clauxel

Gemini Upgrade QA MCP

by clauxel

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    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables coding agents to evaluate a single model over a golden set with trap cases, reporting accuracy overall and on traps, mean latency, cost per request, and failing cases. Also compares a baseline against a candidate model and returns a pass/fail gate verdict with failure reasons, so a model swap can be checked before it ships.
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables you to audit your AI agent skills by running each one against an agent that cannot see it, diffing the resulting artifacts, and grading whether each skill genuinely improves, changes nothing, or worsens the output.
      15 npm
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    • A
      license
      Not graded
      quality
      C
      maintenance
      Provides advanced evaluation tools for assessing AI safety, alignment, and performance of LLM outputs. Enables programmatic evaluation of quality, safety metrics like toxicity and PII detection, and operational metrics including carbon footprint and cost estimation.
      4
      Apache 2.0
    • F
      license
      A
      quality
      B
      maintenance
      Enables LLMs to audit data drift and model degradation in tabular ML pipelines through deterministic statistical tests such as Kolmogorov-Smirnov and Population Stability Index, plus reusable prompts and standards resources.
      4
      -
    • A
      license
      A
      quality
      A
      maintenance
      Enables MCP clients to score retrieval quality with recall, precision, nDCG, hit rate and MRR, compare 2-3 configurations with seeded paired-bootstrap confidence intervals, audit agent tool calls against expected traces, and detect prompt regressions against golden sets. It also generates Markdown, JSON or JUnit reports with pass/fail gates, all deterministically and offline without paid API keys.
      6
      308 npm
      1
      MIT